Home & kitchen case study: ₹40,000 to ₹49,523 monthly revenue in 6 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   We start with marketing and social presence, which the brand in this scenario named first, before anything else on this smaller store. We open with three documents: a website audit, a creative brief and a media schedule by month. We use cart-value tiers so larger baskets earn a better offer.

   Why

   In this case study, a smaller home and kitchen brand grows monthly revenue in 6 months, from ₹40,000 to ₹50L (125x). That is faster than nine in ten of our measured accounts grew over the same time, so the case study below is on what that fastest tenth reached and shows where it lands against the number this scenario calls for. The main problem was marketing and social presence. Later budget calls need something written to be judged against. A larger basket spreads the cost of each order over more revenue.

   How it works

   The brief is agreed first; spend follows it. The tiers follow real order values, not round numbers.

2. 2

   Measurement & reviews · Month 1 to 6

   What we do

   We keep a shared daily sheet with the ad platform's revenue next to real store orders. We agree a written number for every month on the way from ₹40,000 to ₹50L, and start each review with the month-to-date figure against it. We set a written rule: no budget step in a month where return falls too far to pay for it.

   Why

   No starting return on ad spend was given; the starting return is what measured home and kitchen stores of that size hold. Platform attribution over-counts, so budget decisions sit on the store-side number. A shortfall is caught in the month it happens, not at the end.

   How it works

   The sheet is read before each budget change. Each budget step is argued against the written number. Where return slips too far, the month keeps last month's budget.

3. 3

   Creative testing · Month 1

   What we do

   We test with video, catalogue ads and static image first, rising to about two dozen new ads a month by the final month, keeping carousel on a short leash because its return trails the account. We stack kitchen and home interests around a creator video of the lead product. We brief creators for a steady run of UGC video, with regional-language cuts of the winners. We run static images next to the video ads.

   Why

   A demonstration video explains a utility product faster than a static image. A steady supply keeps the testing layer fed, and regional cuts reach more buyers with the same idea. Across measured accounts in all industries, static images reached the top creative tier most often.

   How it works

   The interest stack runs beside a broad audience, read on the same video. Winning UGC is cut into regional languages before new ideas are bought. Statics are added after a video wins. The number of new ads grows with spend; video makes up the largest part and catalogue ads the next.

4. 4

   Scaling · Month 2 to 4

   What we do

   Through Month 2 to Month 4, we push toward ₹50L: the budget rises gently while return holds, and Instagram Reels carries the most spend and Instagram Feed the next. We raise budget only while return on spend holds, and cut it when return drops. We cut regional-language versions of the winning video for the best-selling states.

   Why

   In Month 2 to Month 4 the budget rises gently, while return on spend holds. Budget is part-stepped in three of these months, taking only what return can carry. Each budget step here is sized so that return stays close to where it was. The same winning idea reaches more buyers in their own language.

   How it works

   Each month's budget is set by the return the last one earned. Regional cuts run beside the original winner. In the final month, Instagram Reels takes the most spend and Instagram Feed the next most. Cold audiences take most of the budget; warm audiences return more per rupee.

5. 5

   Steady state · Month 5 to 6

   What we do

   From Month 5, we protect the revenue already built and move toward ₹50L where return permits. We hold a creative bank and swap tired ads out before click-through falls. We build lookalikes from repeat buyers and retarget past buyers with new arrivals.

   Why

   From Month 5 growth slows while revenue is still under ₹50L. Spend still grows, at a slower pace than during scaling. Falling click-through preceded a revenue drop in a measured account, so creative refresh is not optional. Repeat buyers are the cheapest orders an account gets.

   How it works

   Refreshes are gradual: a few new ads at a time. New arrivals go to past buyers first, before broad prospecting.

1. Month 1

   Learning month: a small daily budget carries the first ads, and store orders are matched to tracking. Basket-size offers switch on at checkout. The media schedule and creative brief are signed off.

   • Revenue ₹37,846
   • ROAS 1.89x
   • Ad spend ₹20,042
2. Month 2

   The scaling phase opens: regional-language cuts of the winning UGC go live. The step is sized by what return can bear: return on spend holds while budget steps up.

   • Revenue ₹43,616
   • ROAS 1.90x
   • Ad spend ₹22,905
3. Month 3

   Ads with falling click-through are swapped from the bank. The step is sized by what return can bear: return on spend rises while budget holds.

   • Revenue ₹46,126
   • ROAS 2.00x
   • Ad spend ₹23,108
4. Month 4

   Statics go live next to the winning video.

   • Revenue ₹46,303
   • ROAS 1.87x
   • Ad spend ₹24,696
5. Month 5

   From here the work shifts to keeping ads fresh and bringing buyers back.

   • Revenue ₹47,527
   • ROAS 1.86x
   • Ad spend ₹25,494
6. Month 6

   The budget decision is taken on the return the last step earned. The step is sized by what return can bear: return on spend holds while budget holds. ₹50L is not reached in the time, because budget stops rising where return starts to slip. Each order costs about what it did while learning.

   • Revenue ₹49,523
   • ROAS 1.90x
   • Ad spend ₹26,072

1. 1

   We stack kitchen and home interests around a creator video of the lead product.

2. 2

   Track ad-platform revenue beside store revenue (and net sales) daily or weekly, and set the numbers on the lower figure.

3. 3

   Tested cost caps and bid caps against open bidding